Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses that the tool returns a coverage report with details on addressed control families and counts of controls/mappings, which is useful behavioral context. However, it lacks information on potential limitations, data sources, or performance characteristics (e.g., whether it's read-only, requires authentication, or has rate limits).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences that are front-loaded with the core purpose and efficiently detail the return value. Every sentence adds value without redundancy, making it appropriately sized and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 0 parameters, no annotations, and no output schema, the description provides sufficient context for a read-only analysis tool. It explains what the tool does and what it returns, though it could be more complete by specifying data sources or report format. The lack of output schema means the description must cover return values, which it does adequately.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately does not discuss parameters, focusing instead on the tool's purpose and output. This meets the baseline for tools with no parameters, as it avoids unnecessary details.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('analyze which NIST control families have FedRAMP requirements') and the resource ('coverage report showing which control families are addressed and how many controls/mappings exist for each'). It distinguishes from siblings like 'list_controls' or 'get_control_requirements' by focusing on coverage analysis rather than listing or retrieving specific requirements.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when needing a coverage report of NIST control families with FedRAMP requirements, but does not explicitly state when to use this tool versus alternatives like 'get_control_requirements' or 'list_controls'. No exclusions or prerequisites are mentioned, leaving some ambiguity in context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool computes a diff, implying a read-only comparison, but doesn't specify if it's destructive, requires authentication, has rate limits, or what the output format is. This leaves significant gaps in understanding the tool's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without any wasted words. It's appropriately sized and front-loaded, making it easy to grasp quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of a diff operation with 3 parameters, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It lacks details on parameter meanings, behavioral traits, and output format, making it inadequate for full contextual understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 0%, so the description must compensate for three undocumented parameters. It mentions 'by identifier' which hints at 'id_key', but doesn't explain 'left_path' or 'right_path' (e.g., file paths or document IDs), nor does it clarify the diff structure. This adds minimal semantic value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Compute a structured diff') and the resource ('between two FRMR documents by identifier'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'list_frmr_documents' or 'get_frmr_document', which might handle FRMR documents differently, so it misses full sibling distinction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, such as needing existing FRMR documents, or compare to siblings like 'get_frmr_document' for retrieval, leaving usage context implied at best.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It mentions the tool returns filtered items but lacks critical behavioral details: whether this is a read-only operation, if it requires authentication, rate limits, pagination behavior (implied by limit/offset but not explained), or error handling. The description is minimal and doesn't compensate for the absence of annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded: two sentences that directly state the purpose and result without unnecessary details. Every sentence earns its place by defining the action and outcome clearly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and no output schema, the description is incomplete for a tool with 3 parameters. It doesn't explain return values, behavioral traits, or fully document parameters. For a filtering tool with pagination (limit/offset), more context on output format and usage is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 33% (only 'impact' has a description). The description adds some value by clarifying that 'impact' filters KSI items by level (low, moderate, high), but it doesn't explain the semantics of 'limit' or 'offset' parameters. With low schema coverage, the description partially compensates but leaves two parameters undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Filter Key Security Indicators (KSI) by impact level' with a specific verb ('filter') and resource ('KSI items'). It distinguishes from siblings like 'list_ksi' by specifying filtering by impact level rather than listing all. However, it doesn't explicitly contrast with other filtering tools if they exist.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context by stating 'Returns all KSI items that apply to the specified impact level', suggesting this tool is for retrieving filtered KSI data. However, it provides no explicit guidance on when to use this vs. alternatives like 'list_ksi' or 'get_ksi', nor does it mention prerequisites or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. While it indicates this is a read operation ('Get'), it doesn't mention important behavioral aspects like whether it requires authentication, has rate limits, returns paginated results, or handles errors. The description provides basic function but lacks operational context needed for a tool with no annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is perfectly concise with two sentences that each earn their place: the first states the core purpose, the second specifies the return types. There's zero waste, no redundant information, and it's front-loaded with the most important information first.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter read tool with no output schema, the description provides adequate basic information about what the tool does and returns. However, without annotations covering behavioral aspects and no output schema to describe return format, the description should ideally provide more operational context about authentication, error handling, or result structure to be truly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already fully documents the single 'control' parameter. The description adds marginal value by providing example values ('e.g., AC-2, SC-13, IA-5') which are helpful but essentially repeat what's in the schema. This meets the baseline for high schema coverage where the description doesn't need to compensate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Get all FedRAMP requirements mapped to a specific NIST control') and distinguishes it from siblings by specifying the exact return types ('KSI items and FRMR requirements that reference the control'). It uses precise terminology that differentiates it from tools like 'get_ksi', 'get_frmr_document', or 'list_controls'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context by mentioning what the tool returns (FedRAMP requirements mapped to NIST controls), but doesn't explicitly state when to use this tool versus alternatives like 'get_ksi', 'get_frmr_document', or 'analyze_control_coverage'. It provides some guidance through its specificity but lacks explicit comparison or exclusion statements.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the output includes 'automation-friendly evidence collection sources' and notes the community-sourced nature, but it lacks details on permissions, rate limits, pagination, or error handling. For a tool with no annotations, this leaves significant gaps in understanding its operational behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded, with two sentences that efficiently convey the tool's purpose and an important caveat. Every sentence adds value without redundancy, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (3 parameters, no output schema, no annotations), the description is adequate but incomplete. It explains what the tool returns but lacks details on output format, error cases, or integration with sibling tools. Without annotations or output schema, more behavioral context would improve completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all three parameters thoroughly. The description does not add any parameter-specific semantics beyond what's in the schema, such as examples for 'theme' values or clarification on 'includeRetired'. This meets the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get suggested evidence examples for KSI compliance' with specific details about what it returns ('automation-friendly evidence collection sources') and distinguishes it from official guidance. However, it doesn't explicitly differentiate from sibling tools like 'get_ksi' or 'list_ksi', which might also retrieve KSI-related information.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides minimal usage guidance. It mentions that results are 'community suggestions, not official FedRAMP guidance,' which offers some context on reliability, but it doesn't specify when to use this tool versus alternatives like 'get_ksi' or 'list_ksi' for KSI-related queries, nor does it outline prerequisites or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It describes what the tool returns (metadata, raw JSON, summary) and mentions KSI categories and MAS requirements as examples of content. However, it doesn't disclose important behavioral aspects like error conditions, authentication requirements, rate limits, or response format details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured with three sentences that each add value: stating the tool's purpose, providing usage context, and giving a concrete example. There's no wasted text, and the most important information (what the tool does) comes first.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a retrieval tool with 2 parameters, 0% schema coverage, and no output schema, the description does a good job explaining purpose and usage but lacks details about the return format, error handling, and authentication requirements. The absence of an output schema means the description should ideally explain what the response contains, which it only partially addresses.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description compensates well by explaining the 'path' parameter's purpose and providing a concrete example ('FRMR.KSI.key-security-indicators.json'). It also mentions the 'type' parameter indirectly through the enum values (KSI, MAS, etc.) in the context of what content can be retrieved.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'retrieve' and resource 'FRMR document', specifying what content is returned (metadata, raw JSON, summary). It distinguishes from sibling tools like list_frmr_documents by indicating this is for retrieving specific documents rather than listing available ones.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool ('First use list_frmr_documents to find available documents, then use this tool with the path') and gives a specific example for KSI content. It clearly differentiates from the sibling list_frmr_documents tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool retrieves data (implying read-only), but doesn't cover critical aspects like authentication needs, rate limits, error handling (e.g., what happens if ID doesn't exist), or response format. For a tool with zero annotation coverage, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero wasted words. It front-loads the core purpose ('Retrieve a single KSI entry') and adds necessary qualification ('by id'). Every word earns its place, making it highly concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (1 parameter, no output schema), the description is incomplete. It lacks context about what KSI entries are, their domain (likely compliance/controls based on sibling tools), error scenarios, and response structure. With no annotations and low schema coverage, the description doesn't provide enough information for reliable agent use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It mentions the 'id' parameter and specifies it's used to retrieve a single entry, adding some semantic context beyond the bare schema. However, it doesn't explain the ID format, constraints, or examples, leaving the parameter partially undocumented. This meets the baseline for minimal compensation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Retrieve') and resource ('a single KSI entry'), making the purpose understandable. It distinguishes from sibling 'list_ksi' by specifying retrieval of a single entry by ID rather than listing multiple entries. However, it doesn't explain what 'KSI' stands for or the domain context, which slightly limits clarity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'list_ksi' or 'get_requirement_by_id'. It mentions retrieving by ID but doesn't specify prerequisites, error conditions, or typical use cases. This leaves the agent with insufficient context for optimal tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses the tool's scope (works with three ID types) but doesn't mention behavioral traits like error handling for invalid IDs, response format, or whether it's a read-only operation (implied by 'Get' but not explicit). It adds some context but lacks details on permissions, rate limits, or output structure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the core purpose and followed by specific details on ID formats. Every word earns its place with no redundancy or fluff, making it highly efficient and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (single parameter, no annotations, no output schema), the description is adequate but has gaps. It covers what the tool does and valid inputs, but without annotations or output schema, it should ideally mention that it's a read operation and hint at the return format (e.g., requirement details). It's minimally viable but could be more complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents the single 'id' parameter with examples. The description adds value by specifying the semantic meaning of valid ID formats (KSI-*, FRR-*, FRD-*), which clarifies beyond the schema's generic examples. With 0 parameters beyond the single documented one, this exceeds the baseline of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Get' and the resource 'FedRAMP requirement by its ID', specifying it works with three distinct ID types (KSI indicators, FRR requirements, FRD definitions). This distinguishes it from siblings like get_ksi (which likely returns KSI data generally) or get_control_requirements (which might return requirements for controls).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use this tool: when you have a specific requirement ID from one of the three supported formats. It doesn't explicitly state when NOT to use it or name alternatives, but the specificity of ID-based retrieval implies it's not for listing or searching without IDs.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool aggregates content, implying a read-only operation, but doesn't cover critical aspects like whether it requires authentication, has rate limits, returns structured data, or handles errors. The description is minimal and lacks behavioral context beyond the basic action, making it inadequate for safe and effective use.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action ('Aggregate') and resource ('markdown sections and FRMR references'), making it easy to parse. There's no redundancy or fluff, earning its place as a concise definition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (aggregating content with one parameter), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what the output looks like (e.g., list, compiled text), how 'Significant Change' is defined, or any behavioral traits. For a tool that likely returns data, the absence of output details and minimal context makes it insufficient for reliable agent use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has one parameter 'limit' with a default and range, but schema description coverage is 0%, meaning the schema provides no descriptive context. The description doesn't mention parameters at all, which is acceptable since there's only one parameter and the schema defines it clearly. However, it doesn't add any semantic meaning beyond the schema, such as explaining how 'limit' affects aggregation (e.g., number of results). Given 0% schema coverage and 0 parameters mentioned, the baseline is 4, as the description doesn't need to compensate heavily.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool aggregates markdown sections and FRMR references related to Significant Change, which provides a basic purpose. However, it's somewhat vague about what 'aggregate' entails (e.g., list, compile, summarize) and doesn't clearly differentiate from siblings like 'search_markdown' or 'get_frmr_document', which might handle similar content. The verb 'aggregate' is specific but lacks detail on the output format or scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance is provided on when to use this tool versus alternatives. It mentions 'Significant Change' as a topic, but doesn't specify contexts, prerequisites, or exclusions. Siblings like 'search_markdown' or 'get_frmr_document' might overlap, but the description offers no comparison or usage scenarios, leaving the agent to guess based on tool names alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses the tool's behavior by describing the return content (indicators, impact breakdown, etc.), which is helpful. However, it lacks details on potential limitations (e.g., data freshness, access permissions, error handling) or operational traits (e.g., response format, pagination). The description is informative but not comprehensive for behavioral transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence that front-loads the core action ('Get comprehensive guidance') and efficiently lists the return components. Every part earns its place by clarifying scope and output, with no redundant or vague language. It's appropriately sized for a tool with one parameter and clear functionality.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (one parameter, no output schema, no annotations), the description is largely complete. It explains the purpose, input context, and return content, which suffices for basic use. However, without an output schema, it could benefit from more detail on the return structure (e.g., format of 'impact breakdown'), but the provided information is adequate for the tool's scope.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with the parameter 'theme' well-documented as a KSI theme code with an enum. The description adds value by contextualizing the parameter as the input for retrieving comprehensive guidance, implying it's the primary selector for the summary. Since there's only one parameter and the schema covers it fully, the description compensates adequately without needing to detail syntax or format.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Get') and resource ('comprehensive guidance for a KSI theme'), specifying what the tool does. It distinguishes from siblings by focusing on theme-level summary rather than control-level analysis (e.g., get_control_requirements) or listing functions (e.g., list_ksi). The mention of specific return content (indicators, impact breakdown, NIST controls, documentation links) further clarifies its unique purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when needing comprehensive theme guidance, but does not explicitly state when to use this tool versus alternatives like get_ksi (which might provide different KSI data) or get_control_requirements (which focuses on controls rather than themes). No exclusions or prerequisites are mentioned, leaving usage context somewhat open to interpretation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions searching but doesn't specify if this is a read-only operation, how results are returned (e.g., list of matches, counts), error handling, or performance considerations like rate limits. This leaves significant gaps for a tool with two parameters.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, direct sentence that efficiently conveys the core functionality without unnecessary words. It's front-loaded with the key action and resource, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 2 parameters with 0% schema coverage, no annotations, and no output schema, the description is incomplete. It doesn't explain return values, error cases, or the role of the boolean parameter, leaving the agent with insufficient information for reliable use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the schema provides no parameter details. The description only implies the 'control' parameter is a search term, but doesn't explain its format or the meaning of 'with_enhancements' (e.g., what enhancements are). It adds minimal value beyond the schema, failing to compensate for the coverage gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Search') and target ('markdown files for occurrences of a control identifier'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'search_markdown' or 'search_definitions', which might have overlapping functionality, preventing a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'search_markdown' or 'search_definitions' from the sibling list. It lacks context on prerequisites, such as whether files need to be loaded first, or exclusions, leaving the agent to infer usage scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses what the tool returns (indexed file count, repository path, etc.), which is useful behavioral context. However, it doesn't mention error conditions, performance characteristics, or whether this is a read-only operation (though implied by 'verify' and 'report').

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences: one stating the purpose and one detailing the return values. It's appropriately sized and front-loaded with the core function. However, the second sentence is a bit dense with multiple return items listed, which slightly affects readability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (simple status check with 0 params), no annotations, and no output schema, the description is moderately complete. It explains what the tool does and what it returns, but lacks context on when to use it, error handling, or how it fits with siblings. For a zero-param tool, this is adequate but has gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters, and schema description coverage is 100% (empty schema). The description doesn't need to add parameter semantics, so it meets the baseline of 4 for zero-parameter tools. No additional parameter information is required or provided.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Verify the index is ready and report status.' This is a specific verb ('verify' + 'report') with a clear resource ('the index'). However, it doesn't explicitly differentiate from sibling tools like 'update_repository' or 'list_versions' that might also relate to system status.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, timing (e.g., after updates), or how it differs from other status-related tools in the sibling list. The agent must infer usage from the purpose alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'return' which implies a read operation, but doesn't specify whether this is a query, search, or list operation, nor does it describe output format, pagination, rate limits, or authentication requirements. For a tool with no annotations, this leaves significant behavioral gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that gets straight to the point without unnecessary words. It's appropriately sized for what it communicates, though what it communicates is limited. The structure is clear but could benefit from more detail given the tool's apparent complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 3 parameters with 0% schema coverage, no annotations, no output schema, and multiple sibling tools in the same domain, the description is insufficiently complete. It doesn't explain what 'FRMR sets' are, what 'flattened control mappings' look like, or how the parameters filter results. For a tool that appears to query a specialized compliance/control system, more context is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage and 3 parameters (family, control, source), the description provides no information about what these parameters mean or how they affect the query. The schema shows 'source' has an enum with 13 values, but the description doesn't explain what these sources represent or how they relate to 'FRMR sets'. The description fails to compensate for the complete lack of schema documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the action ('Return') and target ('flattened control mappings across FRMR sets'), which gives a general purpose. However, it's somewhat vague about what 'flattened control mappings' means in practice and doesn't clearly distinguish this tool from siblings like 'get_control_requirements' or 'search_definitions' that might also retrieve control-related information.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. With many sibling tools like 'get_control_requirements', 'search_definitions', and 'list_ksi', there's no indication of how this tool differs in context or when it's the appropriate choice. The description lacks any 'when-to-use' or 'when-not-to-use' information.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden. It discloses the tool's purpose and typical usage pattern but lacks details on behavioral traits like pagination, rate limits, authentication requirements, or error handling. The description is accurate but minimal on behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with zero waste: first states purpose and typical usage, second specifies return types. Front-loaded with key information, appropriately sized for a simple listing tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter listing tool with no output schema, the description provides sufficient context about what data is returned and when to use it. However, it could be more complete by mentioning format of returned metadata or any limitations, though not critical given the tool's simplicity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately focuses on purpose and usage without redundant parameter details, meeting the baseline for zero-parameter tools.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('List') and resource ('FRMR JSON documents and metadata'), specifying the exact data types returned (KSI, MAS, VDR, SCN, FRD, ADS). It distinguishes from siblings like 'get_frmr_document' (retrieves specific document) and 'list_controls' (lists controls rather than documents).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states 'This is usually the first tool to call to discover what FedRAMP data is available,' providing clear when-to-use guidance. It positions this as a discovery tool, distinguishing it from analysis, filtering, or retrieval tools among siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions filtering capability and pagination-like parameters (limit/offset), but doesn't describe what the tool returns (e.g., format, structure), whether it's read-only or has side effects, authentication needs, rate limits, or error conditions. For a listing tool with 6 parameters, this leaves significant behavioral gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately concise with three sentences. The first sentence states the core purpose, the second provides alternative usage guidance, and the third adds clarifying context. Each sentence earns its place, though the structure could be slightly more front-loaded with parameter guidance.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 6 parameters with 0% schema coverage, no annotations, and no output schema, the description is incomplete. It adequately explains the purpose and provides one usage alternative, but fails to address parameter meanings, return values, or behavioral aspects needed for a listing tool with multiple filtering options. The complexity warrants more comprehensive documentation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It mentions 'optional filters' and implies filtering by category, but doesn't explain any of the 6 parameters (id, text, category, status, limit, offset) beyond the generic mention. The description adds minimal value over the bare schema, failing to clarify what these parameters mean or how they work.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'List individual KSI requirement entries' with examples like 'KSI-IAM-01, KSI-CNA-02' and mentions optional filtering. It specifies the resource (KSI requirement entries) and verb (list), but doesn't explicitly differentiate from all siblings beyond mentioning one alternative (get_frmr_document).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use an alternative tool: 'To see all KSI categories and their descriptions, use get_frmr_document with path 'FRMR.KSI.key-security-indicators.json' instead.' This clearly distinguishes between listing specific requirements vs. viewing categories. However, it doesn't mention other potential alternatives among the many sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It mentions 'detected' versions and 'associated metadata', but doesn't disclose behavioral traits like whether this is a read-only operation, how results are formatted, if there are rate limits, or what 'detected' implies (e.g., from a scan vs. a database). This leaves significant gaps for a tool with no annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without any wasted words. It's appropriately sized and front-loaded, making it easy to understand at a glance.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has no parameters, no annotations, and no output schema, the description is minimal but covers the basic purpose. However, it lacks details on behavior, output format, and differentiation from siblings, which are important for completeness in this context with multiple similar tools.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters, and the input schema has 100% coverage (empty object). The description doesn't need to add parameter semantics, so a baseline of 4 is appropriate as it doesn't introduce confusion or redundancy.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'List' and the resource 'detected FRMR versions and associated metadata from documents', which is specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_frmr_documents' or 'list_controls', which would require a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With multiple list-related siblings (e.g., list_frmr_documents, list_controls, list_ksi), there's no indication of context, prerequisites, or exclusions for selecting this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden for behavioral disclosure. It states the tool reads and returns content, but doesn't mention error handling (e.g., if the file doesn't exist), permissions needed, or what 'digest' entails (e.g., a summary or hash). This leaves significant gaps for a tool that interacts with files.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core action and outcome with zero wasted words. It's appropriately sized for a simple read operation.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations, no output schema, and 0% schema description coverage, the description is incomplete. It doesn't explain the return format (what 'contents and digest' means), error conditions, or file access constraints, which are crucial for a file-reading tool in this context with multiple markdown-related siblings.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds no parameter semantics beyond the input schema, which has 0% description coverage. However, with only one parameter ('path'), the baseline is 4, but it's reduced to 3 because the description doesn't clarify what 'path' represents (e.g., file path format, relative vs. absolute) or provide any context beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Read') and resource ('a markdown file'), and specifies what it returns ('contents and digest'). However, it doesn't differentiate from sibling tools like 'search_markdown' or 'grep_controls_in_markdown', which prevents a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'search_markdown' and 'grep_controls_in_markdown' that might handle markdown files differently, there's no indication of when this specific read operation is preferred.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the return format ('matching definitions with their full text and any alternate terms'), which is helpful, but lacks details on permissions, rate limits, error handling, or pagination. For a search tool with zero annotation coverage, this is insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence that efficiently conveys the tool's purpose and output. It's front-loaded with the core functionality and avoids unnecessary details, making it highly concise and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose and return format but lacks details on usage context, parameter behavior, and operational constraints. Without annotations or output schema, more completeness is needed for a higher score.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 50% (only the 'term' parameter has a description). The description adds no additional parameter semantics beyond what's in the schema—it doesn't explain search behavior (e.g., exact match, partial match, case sensitivity) or the 'limit' parameter's effect. With moderate schema coverage, the baseline is 3, as the description doesn't compensate for gaps.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Search FedRAMP definitions (FRD document) by term.' It specifies the verb ('search'), resource ('FedRAMP definitions'), and scope ('FRD document'). However, it doesn't explicitly differentiate from sibling tools like 'search_markdown' or 'grep_controls_in_markdown', which limits it to a 4 rather than a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'search_markdown' or 'grep_controls_in_markdown', nor does it specify prerequisites, exclusions, or contextual usage. This lack of comparative guidance results in a low score.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the tool's function but lacks details on behavioral traits such as rate limits, authentication requirements, error handling, or the format of search results. The mention of 'Full-text search' implies a read-only operation, but this is not explicitly stated.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured, with two sentences: the first states the purpose and usage, and the second provides examples. Every sentence adds value without redundancy, making it easy to understand quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (a search function with 3 parameters) and the lack of annotations and output schema, the description is incomplete. It covers the purpose and usage well but misses details on parameters, behavioral traits, and result format, which are essential for effective tool invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 0%, so the description must compensate for undocumented parameters. It does not mention any parameters explicitly, but the examples ('continuous monitoring', etc.) implicitly relate to the 'query' parameter. However, it provides no guidance on 'limit' or 'offset' parameters, leaving gaps in understanding their use.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Full-text search') and resource ('FedRAMP markdown documentation and guidance'), and it distinguishes this from siblings by specifying the search domain. It provides concrete examples of search terms to illustrate its function.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use this tool ('to find information about policies, procedures, requirements, and guidance') and provides examples of search queries. However, it does not mention when not to use it or name specific alternatives among the sibling tools, such as 'search_definitions' or 'grep_controls_in_markdown'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden and does well by explaining the tool's behavior: it's a forced update operation that fetches from GitHub, resets to latest version, and may require server restart or index rebuild. It doesn't mention error conditions or rate limits, but covers the main behavioral aspects adequately.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured with three sentences that each add value: first states purpose, second explains timing context, third provides post-execution guidance. No wasted words or redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter tool with no annotations or output schema, the description provides comprehensive context about what the tool does, when to use it, and post-execution considerations. It could mention potential side effects more explicitly, but covers the essential information well.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, focusing instead on the tool's behavior and usage context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Force update'), target resource ('cached FedRAMP docs repository'), and purpose ('to get the latest data'). It distinguishes this tool from all sibling tools by focusing on repository maintenance rather than document analysis, filtering, or searching.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use this tool ('to update immediately' instead of waiting for the automatic 24-hour check) and provides post-update guidance ('you may need to restart the MCP server or rebuild the index to see changes'). It clearly differentiates from the automatic background process.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.